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10.5120/ijca2016911312 |
Abstract
With the growing increase of the utilization of technology in sports; our novel project the Umpire gesture Recognition System aims squarely to introduce a more robust technology to show Umpire choices with the assistance of Gesture Recognition and trailing of hand movement of the Umpire. This technology helps to alleviate the burden of the score-keepers. It conjointly minimizes errors in displaying Umpire choices therefore adding to a more robust viewing expertise. This paper presents four easy but economical ways to implement hand gesture recognition specifically Subtraction, Gradient, Principal elements Analysis and Rotation Invariant. The ways used were in to retrieve the right matches. The results supported speed and accuracy was analysed.
References
- Xia Liu and Kikuo Fujimura, “ Hand Gesture Recognition using Depth Data”, Proc. of the Sixth IEEE International conference on automatic Face and Gesture Recognition, pp. 529-534, 2004.
- L. Bretzner, I. Laptev, and T. Lindeberg, “Hand Gesture using multi-scale color features, hierarchical models and particle filtering”, Proc. of the Fifth International conference on Automatic Face and Gesture Recognition, pp. 423- 428, 2003.
- V. Pavlovic, et al. visual interpretation of hand gesture for human-computer interaction: a review, IEEE Trans. On Pattern anal. Mach. Intel. 19(7), pp 677-695, 1997.
- Attila Licsar and TamasSziranyi, “Supervised training based hand gesture recognition system”, Proc. of the 16th International Conference on Pattern Recognition, Vol. 3, pp 30999 – 31003, 2002.
- Chambers, Graeme S., Venkatesh, Svetha, West, GeoffA.W. and Bui, Hung H. 2004, Segmentation of intentional human gestures for sports video annotation, in MMM 2004 :Proceedings of the 10th International Multimedia Modelling Conference, IEEE Computer Society, Los Alamitos, Calif., pp. 124-129.
Keywords
Gestures, Umpire, Cricket, Euclidean, Eigen Vector,Gradient, GUI,